Normal gut microbiota modulates brain development
Rochellys Diaz Heijtza,b,1, Shugui Wangc, Farhana Anuard, Yu Qiana,b, Britta Björkholmd, Annika Samuelssond,
Martin L. Hibberdc, Hans Forssbergb,e, and Sven Petterssonc,d,1
Departments ofaNeuroscience, anddMicrobiology, Cell and Tumor Biology, Karolinska Institutet, 171 77 Stockholm, Sweden;bStockholm Brain Institute, 171
77 Stockholm, Sweden;cGenome Institute of Singapore, 02-01 Genome 138672, Singapore; andeDepartment of Women’s and Children’s Health, Karolinska
Institutet, 171 76 Stockholm, Sweden
Edited by Arturo Zychlinsky, Max Planck Institute for Infection Biology, Berlin, Germany, and accepted by the Editorial Board January 4, 2011 (received for
review August 11, 2010)
Microbial colonization of mammals is an evolution-driven process
that modulate host physiology, many of which are associated with
immunity and nutrient intake. Here, we report that colonization
by gut microbiota impacts mammalian brain development and
subsequent adult behavior. Using measures of motor activity and
anxiety-like behavior, we demonstrate that germ free (GF) mice
display increased motor activity and reduced anxiety, compared
with specific pathogen free (SPF) mice with a normal gut micro-
biota. This behavioral phenotype is associated with altered expres-
sionof genes known tobe involvedin secondmessenger pathways
and synaptic long-term potentiation in brain regions implicated in
motor control and anxiety-like behavior. GF mice exposed to gut
microbiota early in life display similar characteristics as SPF mice,
including reduced expression of PSD-95 and synaptophysin in the
striatum. Hence, our results suggest that the microbial colonization
process initiates signaling mechanisms that affect neuronal circuits
involved in motor control and anxiety behavior.
developmental programming|microbiome|basal ganglia|cognitive
organism’s later development, structure, and function. This
phenomenon is called “developmental programming,” a process
whereby an environmental factor acting during a sensitive or vul-
and function of organs that, in some cases, will persist throughout
life (1). One such environmental factor is the gut microbiota that,
because of an evolutionary process, has adapted to coexist in com-
mensal or symbiotic relationship with mammals (2). Immediately
after birth, the newborn organism is rapidly and densely populated
with complex forms of indigenous microbes. This process has been
shown to contribute to developmental programming of epithelial
barrier function, gut homeostasis, and angiogenesis, as well as the
innate and host adaptive immune function (3, 4). Recent data
indicate that gut microbiota have systemic effects on liver function
(5–7), thus raising the possibility that gut microbiota can have de-
velopmental effects in other organs elsewhere in the body.
The functional development of the mammalian brain is of par-
ticular interest becauseit has been shown to be susceptible to both
internal and external environmental cues during perinatal life.
Epidemiological studies have indicated an association between
common neurodevelopmental disorders, such as autism and
schizophrenia, and microbial pathogen infections during the peri-
natal period (8, 9). These findings are supported by experimental
studies in rodents, demonstrating that exposure to microbial
pathogens during similar developmental periods result in behav-
ioral abnormalities, including anxiety-like behavior and impaired
cognitive function (10–12). In a recent study, it was shown that the
commensal bacteria, Bifidobacteria infantis, could modulate tryp-
tophan metabolism, suggestingthat thenormal gutmicrobiotacan
influence the precursor pool for serotonin (5-HT) (13).
Here, we tested the hypothesis that the “normal” gut micro-
biota is an integral part of the external environmental signals
that modulate brain development and function.
Germ Free (GF) Mice Display Increased Motor Activity and Reduced
Anxiety-Like Behavior. In the first set of experiments, we subjected
adult GF and specific pathogen free (SPF) mice with a normal
gut microbiota to a battery of tests for exploratory activity and
anxiety. GF and SPF mice were placed in a novel, open-field
activity box. Their spontaneous motor activity, including loco-
motor and rearing activities, were measured for 60 min. GF mice
showed greater total distance traveled and more exploration of
the center of the open field (P < 0.05; Fig. 1A). There was also
a trend for GF to display higher levels of rearing activity com-
pared with SPF (GF vs. SPF, 489 ± 43 vs. 369 ± 50, P = 0.088).
Both GF and SPF mice displayed similar locomotor activity (Fig.
1B) during the initial open field exposure, indicating that the
increased locomotor activity in GF mice was not triggered by
novelty. Instead, significant differences between groups were
detected in habituation over time (repeated measures ANOVA,
main effect F(1, 70)= 6.28, P < 0.05). Thus, GF mice traveled
a significantly longer distance (Fig. 1 B and C) and spent sig-
nificantly (P < 0.05) more time in both slow and fast locomotion
(Fig. 1D) during the 20- to 60-min interval of testing.
Given that certain microbial pathogens have been reported to
induce anxiety-like behavior in animal models (10–12), we
assessed whether the nonpathogenic gut microbiota could also
affect anxiety-like behavior. For this purpose, we used two rodent
tests of anxiety: the light–dark box test andthe elevated plus maze
(14). In the light–dark box test, GF mice spent significantly (P <
0.05) more time in the light compartment of the box than control
SPF mice (Fig. 2A). In the elevated plus maze test, GF mice spent
significantly (P < 0.05) more time in the open arm than SPF mice
(Fig. 2B and Movies S1 and S2). The GF mice also engaged in
(GF vs. SPF: 3.9 ± 0.6 vs. 1.4 ± 0.69, P < 0.05) to the ends of the
open arms. There were no significant differences in the number of
entries (GF vs. SPF: 13.14 ± 0.9 vs. 14.4 ± 1.5, P > 0.1) and time
spent (Fig. 2B) in the closed arm between GF and SPF mice.
To test whether conventionalization in early life of GF mice
could “normalize” the increased motor activity and alter the
anxiety behavior, we conventionalized a new set of GF mice with
microbiota obtained from SPF mice 30 d before mating and
allowed the progeny to mature in an isolator with bacteria. Adult
conventionalized offspring (CON) were behaviorally tested as
described above. The rearing activity of the CON mice was sig-
Author contributions: R.D.H., F.A., B.B., H.F., and S.P. designed research; R.D.H., S.W., F.A.,
Y.Q., and A.S. performed research; R.D.H., S.W., F.A., Y.Q., B.B., M.L.H., H.F., and S.P.
analyzed data; and R.D.H., F.A., H.F., and S.P. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission. A.Z. is a guest editor invited by the Editorial
Freely available online through the PNAS open access option.
1To whom correspondence may be addressed. E-mail: email@example.com or sven.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
| February 15, 2011
| vol. 108
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nificantly different from that of GF mice (P < 0.05) and did not
differ from that of SPF mice (Fig. 1E).
CON mice normalized their locomotor activity to that of SPF
mice during the later time interval of testing (P < 0.05; Fig. S1),
whereas their initial locomotor activity was similar to that of GF
mice. In the light–box test, the behavioral pattern of CON mice
of SPF mice (P < 0.05; Fig. S2). In the elevated plus maze test, the
GF mice spent significantly (P < 0.05) more time exploring the
open arms compared with SPF mice. Introducing microbiota
early in life to GF mice showed that CON mice altered their
behavior and spent less time exploring the open arms (Fig. S3).
could normalize several behavioral patterns of GF mice, we ex-
plored whether there is a sensitive/critical period for the effects of
the normal gut microbiota on behavior. We therefore con-
test as described above. Notably, conventionalization of adult mice
failed to normalize the behavior of GF mice (Fig. 1F and Fig. S4).
GF Mice Show Elevated Noradrenaline (NA), Dopamine (DA), and 5-HT
Turnover in the Striatum. Anxiety-like behavior has been associ-
ated with alterations in monoamine neurotransmission. There-
fore, we investigated potential changes in the neurochemistry of
GF mice in a new set of animals. The concentration of nor-
adrenaline (NA), dopamine (DA), and 5-HT and their major
metabolites, 3-methoxy-4-hydroxyphenylglycol (MHPG), dihy-
droxyphenylacetic acid (DOPAC), and homovanillic acid (HVA),
and 5-hydroxyindoleacetic acid (5-HIAA), were measured in
frontal cortex, striatum, and hippocampus of GF and SPF mice.
The turnover rate of NA, DA, and 5-HT was significantly higher
in the striatum of GF mice compared with SPF mice (Fig. 3). In
contrast, no significant differences were found in the frontal
cortex or hippocampus (Table S1).
GF Mice Show Altered Expression of Synaptic Plasticity-Related
Genes. Previous molecular and behavioral studies have impli-
cated the immediate-early gene, nerve growth factor-inducible
clone A (NGFI-A), and the synaptic plasticity-related gene,
activity. (A) Bars show cumulative distance traveled
(meters) per zone and in the entire box (total) during the
60-min open field test session by SPF (open bars) and GF
(filled bars) mice. (B) Average distance traveled (meters)
measured in 10-min time bins across a 60-min session in
an open field box. (Inset) Bars show cumulative distance
traveled (meters) during the initial 10 min and the 20- to
60-min time interval of open field testing. (C) Represen-
tative tracks of movement patterns of SPF and GF mice at
the 0–10, 30–40, and 50–60 min time intervals of the
60-min open field test session; distance traveled and
rearing activity is shown in dark red and blue colors, re-
spectively. (D) The time that SPF and GF mice spent in
slow (>5 cm/s) or fast (>20 cm/s) locomotion during the
initial 10 min of testing and the 20–60 min time interval.
(E) Rearing activity of SPF (white), GF (black), and con-
ventionalized (CON; light gray) mice. Circles show the
average number of rears measured in 10-min time bins
across a 60-min session in an open field box. (F) Rearing
activity of SPF, GF, and adult CON mice (dark gray); lines
connecting cumulative data in B, E, and F were drawn for
clarity only. All data (A, B, and D–F) are presented as
means (± SEM; n = 7–14 per group). *P < 0.05 compared
with SPF mice.
GF mice display increased spontaneous motor
(seconds) spent in the light and dark compartments during a 5-min light–
dark box test by the SPF and GF mice. (B) Bars show time (seconds) spent in
each area of the elevated plus maze by the SPF and GF mice during a 5-min
test session. All data (A and B) are presented as means (±SEM; n = 7–9 per
group). *P < 0.05 compared with SPF mice.
GF mice display reduced anxiety-like behavior. (A) Bars show time
| www.pnas.org/cgi/doi/10.1073/pnas.1010529108Diaz Heijtz et al.
brain-derived neurotrophic factor (BDNF), in the development
of anxiety-like behavior (15–17). We therefore studied the ex-
pression of these genes in the frontal cortex, striatum, amygdala,
and hippocampus of GF and SPF mice, by means of in situ hy-
bridization technique. In GF mice, NGFI-A mRNA expression
was significantly lower in various subregions of the prefrontal
cortex, including the orbital frontal cortex (Fig. 4 A and A′); as
well as in the striatum (GF vs. SPF: 329 ± 33 vs. 586 ± 18, P <
0.0001), hippocampus (CA1 region, GF vs. SPF: 258 ± 15 vs.
499 ± 22, P < 0.0001; CA3 region, GF vs. SPF: 166 ± 13 vs. 236 ±
6, P < 0.001; dentate gyrus, GF vs. SPF: 76 ± 4 vs. 113 ± 5, P <
0.0001) and amygdala (GF vs. SPF: 126 ± 17 vs. 212 ± 19, P <
0.01) compared with SPF mice. Similarly, GF mice had signifi-
cantly lower BDNF mRNA expression in the hippocampus,
amygdala (Fig. 4 B and B′), and cingulate cortex (GF vs. SPF:
162 ± 6 vs. 193 ± 10, P < 0.05), which are key components of the
neural circuitry underlying anxiety and fear (18).
Given that DA is an important regulator of motor and cog-
nitive functions (19), we examined the expression of dopamine
receptors (D1 and D2 receptors) and intracellular signaling
mechanisms (i.e., DARPP-32) in the above regions. In GF mice,
DA D1 receptor mRNA was significantly (P < 0.05) higher in the
hippocampus (Fig. 4 D and D’), while lower in the striatum and
nucleus accumbens, albeit without significance (Fig. 4 C and C’)
compared with SPF mice. There were no significant differences
in the expression of DARPP-32 or DA D2 receptors between GF
and SPF mice.
GF Mice Show Alterations in Genes Involved in Four Canonical
Pathways. Having established that the normal gut flora could
modify behavior and gene expression in key brain regions, we
applied the gene expression profiling technique to assess whether
other genes were subject to modulation by gut microbiota. The
gene expression patterns of five brain regions of 11 mice (5 GF
mice and 6 SPF mice) were profiled. Genes differentially
expressed between GF and SPF mice (with significant fold
changes >2) were used to generate heat maps by using Cluster
and Tree View software. The gene expression profile was very
consistent across independent tissue samples of the same brain
region (see patterns of green or red color). In the hippocampus,
we found 50 genes to be significantly differentially expressed
(45 genes were higher and 5 were lower in GF mice compared
with SPF mice; Fig. 5A). Moreover, 20 and 23 genes were sig-
nificantly, differentially expressed in the cortex and striatum,
respectively (Fig. 5B and C). In addition, 84 genes were differ-
entially expressed in the cerebellum and only 1 gene in hypo-
thalamus. For quantitative real-time PCR (Q-PCR) confirmation
of microarray data, we selected 44 genes of the modulated genes
described above and 6 candidate genes implicated in the be-
havioral phenotype of GF mice. We confirmed 38 of these 50
genes to be differentially expressed (35 in hippocampus, 11
in cortex, and 4 in striatum), with three genes common to all
regions (Indo, Tlr1, and Gna1) (Table S2–S4). These gut
microbiota-regulated genes were characterized into four statis-
tically significant canonical pathways (Fig. 5D).
Gut Microbiota Colonization of GF Mice Reduces Protein Expression of
Synaptophysin and PSD-95 in Striatum. In an attempt to identify
whether specific proteins connected to synaptogenesis would be
subject to gut microbiota regulation and, thereby, provide a possi-
ble mechanism for the observed alteration of brain function, we
investigated the protein expression of PSD-95 and synaptophysin
in the frontal cortex, striatum, and hippocampus of GF, SPF,
ofbothsynaptophysinandPSD-95 inthe striatumwassignificantly
lower (P < 0.05) in SPF and CON mice compared with GF mice.
However, there were no differences in the expression of synapto-
physin or PSD-95 in frontal cortex and hippocampus.
turnover in the striatum. The histograms depict the
mean ratios (± SEM; n = 6 per group) for MHPG/NA
(A), DOPAC/DA (B), and 5-HIAA/5-HT (C) in the
striatum of male GF and SPF mice. Asterisks denote
where GF mice differ significantly (P < 0.01) from
GF mice show elevated NA, DA, and 5-HT
related genes. (A) Representative autoradiograms showing NGFI-A mRNA
expression at the level of the frontal cortex of SPF and GF mice (OFC, orbital
frontal cortex; AO, anterior olfactory region). (A’) Bars show expression of
NGFI-A mRNA (nCi/g) in the OFC and AO of SPF and GF mice. (B) Represen-
tative autoradiograms showing BDNF mRNA expression at the level of
amygdala and dorsal hippocampus of SPF and GF mice (BLA, basolateral
amygdala; CA1, CA1 region of the dorsal hippocampus). (B’) Bars show ex-
pression ofBDNF mRNA (nCi/g) inthe BLA and CA1regionof SPF andGF mice.
(C) Representative autoradiograms showing dopamine D1 receptor (Drd1a)
mRNA expression at the level of the striatum and nucleus accumbens of SPF
and GF mice (STR, striatum; Accb, nucleus accumbens, shell region). (C’) Bars
show expression of Drd1a mRNA (nCi/g) in the STR and Accb of SPF and GF
mice. (D) Representative autoradiograms showing Drd1a mRNA expression at
the level of the dorsal hippocampus of SPF and GF mice (DG, dentate gyrus;
PtCx, parietal cortex,somatosensoryarea).(D’)Bars show expression ofDrd1a
mRNA (nCi/g) in the DG and PtCx of SPF and GF mice. All data (A’–D’) are
expressed as means ± SEM, n = 8 per group. Filled bars represent GF mice.
Open bars represent SPF mice. *P < 0.05, *P < 0.001 compared with SPF mice.
GF mice show altered expression of anxiety and synaptic plasticity-
Diaz Heijtz et al.PNAS
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This study supports the hypothesis that normal gut microbiota
can affect normal brain development and behavioral functions.
Our data extend previous observations from Sudo and coworkers
who demonstrated that gut microbiota could modulate the levels
of adreno-corticotrophic hormone (ACTH) in young mice (20),
as well as findings from the Gordon laboratory reporting ele-
vated home-cage activity counts in GF mice (21). Here, we
propose that altered expression profiles of canonical signaling
pathways, neurotransmitter turnover, and synaptic-related pro-
teins may combine and contribute to behavioral differences ob-
served between SPF and CON mice compared with the GF mice.
Synaptophysin is a synaptic vesicle glycoprotein, which is ex-
pressed in neuroendocrine cells and in most neurons in the central
nervous system. It is a hallmark ofsynaptic vesicle maturation (22),
and it is also considered an indirect marker of synaptogenesis in
the developing brain (23). Likewise, PSD-95 is involved in the
maturation of excitatory synapses (24). In line with a window of
opportunity early in life, it is plausible that the gut microbiota was
able to modulate both synaptophysin and PSD-95 in the striatum
during a sensitive period of synaptogenesis. Therefore, the mod-
ulation of these proteins by the gut microbiota could lead to long-
term modulation of synaptic transmission affecting motor con-
trol and anxiety-like behavior in adult life. The perinatal period
appears to be critical for this type of developmental programming
because the ability of the gut microbiota to modulate, e.g., the
exposedtothe gutmicrobiota earlyduring postnatal development
(i.e., before 6 wk of age) (20). The present data also support the
between SPF (n = 6) and GF (n = 5) mice in the hippocampus (A), frontal cortex (B), and striatum (C). Each row represents the relative levels of expression of
a single gene across all mice; each column represents the levels of expression for a single mouse. The colors red and green denote high and low expression,
respectively. Differentially expressed genes were investigated for functional clustering by using Ingenuity Pathway Analysis software for canonical pathways
(D), as described in Experimental Procedures.
Expression profiling of GF mice and SPF mice brains. A heatmap of genes showing statistically significant (q < 5%) and fold change (>2) differences,
related proteins in the striatum compared with SPF
mice. Representative Western blot films for syn-
aptophysin (A) and PSD-95 (B) protein expression in
the frontal cortex, striatum, and hippocampus of
two male GF, SPF, and CON mice (for further details,
see Table 1).
GF mice show higher expression of synaptic-
| www.pnas.org/cgi/doi/10.1073/pnas.1010529108Diaz Heijtz et al.
to affect later-life brain and behavior. Interestingly, nonhuman
primate studies have demonstrated that administered glucocorti-
coids reduce synaptophysin expression in the fetal brain (25).
Hence, modulation of stress hormones (e.g., ACTH and cortico-
sterone) by the gut microbiota is another potential mechanism
that could explain the present findings.
Another possible mechanism mediating the gut-brain com-
munication, proposed here, may be via established neuronal
circuits. Gut microbiota can elicit signals via the vagal nerve to
the brain and vice versa (26, 27). Modulation of transmitters
(e.g., serotonin, melatonin, gamma-aminobutyric acid, histamines,
and acetylcholine) within the gut is yet another possible mech-
anism of action that could mediate the effects of the gut
microbiota. For example, metabolic profiling of GF and con-
ventionalized mice have revealed that conventionalization of GF
mice by gut microbiota results in a 2.8-fold increase in plasma
serotonin levels (28). This increase may arise from peripheral
serotonin pools stored in the colon that, upon exposure to the
incoming gut microbiota during early postnatal life, are released
(29). Thus, this postnatal developmental change induced by the
gut microbiota creates system conditions by which periphery
pools of serotonin are carefully monitored and tightly regulated
in early postnatal development. It is intriguing that the same
neurotransmitter pathway is involved in the regulation of both
food intake (30) bone remodeling (31) and behavioral brain
functions (32). Recent data have demonstrated similar cross-talk
between food intake, innate immunity, and G-coupled receptors
expressed in the nervous system of Caenorhabditis elegans (33).
Although the mechanisms outlined above may help to explain
how gut microbiota could modulate brain development and
in brain observed in the present study, i.e., regulation of synaptic-
associated proteins and neurotransmitter turnover specifically in
the striatum. Within this context, it is worth mentioning that some
bacteria (e.g., Clostridium botulinum and Clostridium tetani) are
known to produce neurotoxins that specifically target a group of
proteins that enable synaptic vesicles to dock and fuse with pre-
synaptic plasma membranes. In the present study, we also found
that the normal gut microbiota target two key synaptic pro-
teins, namely synaptophysin and PSD-95 in the striatum. Recent
data indicate that pattern recognition receptors expressed on the
microglia surface characterize one of the primary, common path-
ways by which neurotoxin signals affect neuronal tissues (34).
Interestingly, there seems to be a great diversity in microglia
phenotype and function (35). Therefore, microglia cells could be
involved in the signaling pathways induced by normal gut micro-
Our results suggest that during evolution, the colonization of
gut microbiota has become integrated into the programming of
brain development, affecting motor control and anxiety-like be-
havior. It is tempting to speculate that the differences that we
observe between GF and SPF mice are mediated by signaling
initiated soon after birth at a time when the newborn mice be-
come exposed to gut microbiota. This suggestion does not ex-
clude the possibility that exposure to gut microbiota metabolites,
generated by the flora of the pregnant mother, could also in-
fluence brain development during embryogenesis.
Gut microbiota may also be able to modify expression of risk
genes (16, 36) or be part of mechanisms that alter cognitive func-
tions observed in patients with gastrointestinal diseases (37, 38).
Finally, the observed behavioral changes imposed by the presence
of the gut flora in rodents, reported in this paper, may have wider
implications when considering psychiatric disorders in humans.
Animals. Newborn litters of GF and SPF NMRI mice were placed and raised in
special plastic isolators until they reached 8 to 10 wk of age (Core Facility for
Germ Free Research, Karolinska Institutet). Only male animals were used in
these experiments. Animals were maintained on autoclaved R36 Lactamin
Chow (Lactamin) and kept in 12-h light cycles. All procedures were approved
by the Local Research Ethics Committee.
Behavioral Studies. Testing took place between 0900 and 1500 hours under
insterilefiltered cages to an adjacent testing room and allowed to rest for 1 h
before testing. Test chambers were cleaned first with disinfectant and then
with 70% ethanol and water after each animal.
Open Field Test. Animals were placed individually in the center of an open
field box (48 cm × 48 cm; Acti-Mot detection system; TSE), and their spon-
taneous motor activity was recorded as described (39). The computer pro-
gram automatically recorded the following parameters: distance traveled in
the center, periphery and total (entire box), a count of rearing activity
(vertical infrared photo beam breaks), and time spent in slow (>5 cm/s, with
an upper range of 20 cm/s) or fast (>20 cm/s) locomotion.
Light–Dark Box Test. In this test, the mouse was placed into the dark com-
partment and allowed to freely explore the apparatus (48 × 48 cm; with two
zones of equal areas) for 5 min. Time spent in the dark and light compart-
ments were measured by using photocells (TSE).
Elevated Plus Maze Test. The elevated plus maze, made of dark gray glacial
polyvinyl chloride, consisted of four arms (each 30 × 5 cm) and a central area
(5 × 5 cm) elevated 50 cm above the floor. Two arms were open and two
were closed with 10-cm-high walls made of the same material. Mice were
individually placed in the center facing an open arm and allowed to explore
for 5 min. The behavior of the animal was recorded with a video camera and
later scored by two independent observers that were blind to the identity of
the animals. The following behaviors were scored: open and closed arm
entries, time spent in the closed and open arms and in the center, and ex-
ploration of open arm ends.
Behavioral Analysis. The behavioral data from the open field test were an-
alyzed by using either repeated measures analysis of variance (ANOVA;
phenotype and time as main factors) or factorial ANOVA when appropriate.
The behavioral data from the light–dark box and elevated-plus maze tests
were analyzed by using one-way ANOVA. All post hoc comparisons were
made with Bonferroni/Dunn test in the presence of significant ANOVA
effects. The threshold for statistical significance was set as P ≤ 0.05.
Neurochemical Analysis. Brain samples were analyzed at Pronexus Analytical
AB (Karolinska Institutet Science Park, Stockholm). Briefly, tissue concen-
tration of NA, MHPG, DA, DOPAC, HVA, 5-HT, and 5-HIAA were determined
by reversed-phase high-performance liquid chromatography with electro-
Expression of synaptophysin and PSD-95 in various brain regions of GF, SPF, and CON
Synaptophysin PSD-95SynaptophysinPSD-95 SynaptophysinPSD-95
0.989 ± 0.058
1.000 ± 0.062
0.992 ± 0.022
1.039 ± 0.085
1.000 ± 0.145
1.011 ± 0.090
1.803 ± 0.037*
1.000 ± 0.015*
1.013 ± 0.028*
2.171 ± 0.042*
1.000 ± 0.036*
1.001 ± 0.063*
0.982 ± 0.046
1.000 ± 0.051
0.973 ± 0.039
1.025 ± 0.136
1.000 ± 0.075
1.045 ± 0.076
Expression of synaptophysin and PSD-95 in the frontal cortex, striatum, and hippocampus of GF (n = 4), SPF
(n = 4), and CON (n = 6) mice were quantified and calculated against their respective actin expression (Fig. 6). The
values were then compared against the SPF mice values and expressed as average fold increase. Values are
expressed as means ± SEM.
*P < 0.05 compared with SPF mice.
Diaz Heijtz et al.PNAS
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| vol. 108
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chemical detection as described (40). Data were analyzed by using one-way Download full-text
ANOVA. Post hoc comparisons were made with Bonferroni/Dunn test.
at −80 °C. Coronal sections (14 μm) of various brain regions (frontal cortex,
striatum, hippocampus, and amygdala) were prepared on a cryostat and
stored at −80 °C until used. Fixation, prehybridization, and hybridization
were performed as described (ref. 39; see SI Experimental Procedures for in-
formation about synthesis of riboprobes and quantification procedure).
Illumima Expression Array. Brain tissues (frontal cortex, striatum, hypothal-
amus, hippocampus, and cerebellum) were rapidly dissected and stored at
−80 °C until used. RNA was extracted by using Qiagen RNA extraction kit.
The RNA (0.5 μg) was amplified and labeled by using Illumina total prep RNA
amplification kit (Ambion). cRNA (0.75 μg) were applied on Illumina chips
(Mouse chips Ref.V1.1) according to the manufacturer’s instruction. After
hybridization and washing, each array was scanned by Illumina’s scanning
software (BeadScan) to produce an image in the Tagged Image File Format,
along with files in a proprietary file format containing intensity and location
information. Original data were extracted and normalized by using Bead-
Studio software. After normalization, probe signals were checked for de-
tection against negative controls with a BeadStudio internal algorithm and
missing values were introduced to replace signals under the detection limit.
Probes that failed to detect signal in at least three mice were filtered out.
Further data analysis was applied on Gene Spring, where probes with low
detection values (<50) or low confidence detection (P < 0.99) were further
filtered out. Genes differentially expressed more than twofold were selected
and used for statistical analysis (one-way ANOVA) to select for significance
(P < 0.05). Lists of statistically, differentially expressed genes were then ana-
lyzed by using Ingenuity Pathway Analysis, Cluster, and Tree View software.
Western Immunoblotting. Brain tissues were dissected on ice frozen by liquid
nitrogen and stored at −80 °C. Tissue samples were homogenized in ice-cold
RIPA lysis buffer [50 mM Tris at pH 7.4, 150 mM NaCl, 1% (wt/vol) Nonidet P-
40, 0.5% (wt/vol) sodium deoxycholate, 1 mM EDTA, 0.1% (wt/vol) SDS] in
the presence of protease inhibitors (1 mM PMSF; 10 μg/mL chymostatin,
leupeptin, antipain and pepstatin A; and 2 μg/mL aprotinin). After centri-
fugation at 4 °C, 25 μg of protein were mixed with reducing sample buffer,
denatured, and subjected to electrophoresis (7.5–15% SDS/PAGE gels) fol-
lowed by electroblotting onto presoaked PVDF membranes (BioRad). Blots
were blocked in 0.1% Tween-20, 5% milk in PBS, at room temperature.
Primary antibodies synaptophysin and PSD-95 (Cell Signaling) were in-
cubated with the blot o/n at 4 °C. Incubation with horseradish peroxidase-
conjugated secondary antibodies (Amersham Pharmacia) was performed at
room temperature. Protein bands were visualized by chemiluminescence by
using Super Signal West Pico Chemiluminescent Substrate (Pierce) reagent.
Protein expression of synaptophysin and PSD-95 were then quantified by
using ImageJ software. Group differences were analyzed by using separate
Student’s t test from each protein.
Q-PCR. Expression of genes of interest, including genes from microarray re-
sults (Table S1–S3), were quantitatively measured by using TaqMan real-time
PCR system as previously described (4). The unpaired Student’s t test was used
for statistical analyses. The level of statistical significance was set at P ≤ 0.05.
ACKNOWLEDGMENTS. This work was supported by the Swedish Research
Council, Vinnova, and the Swedish Foundation for Strategic Research (S.P.
and H.F.); the Söderberg Foundation and the 7th EU program TORNADO
(S.P.); Foundation Olle Engkvist Byggmästare (H.F.); and Foundation Frimur-
are Barnhuset (R.D.H.). F.A. holds a postdoctoral fellowship from A*STAR
Singapore. M.L.H. and S.W. were supported by A*STAR.
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| www.pnas.org/cgi/doi/10.1073/pnas.1010529108 Diaz Heijtz et al.